While pregnancy may accelerate glioblastoma multiforme (GBM) growth, parity and progesterone (P4) containing treatments (ie, hormone replacement therapy) reduce the risk of GBM development. In parallel, low and high doses of P4 exert stimulating and inhibitory actions on GBM growth, respectively. The mechanisms behind the high‐dose P4‐suppression of GBM growth is unknown. In the present study, we assessed the changes in growth and proteomic profiles when high‐dose P4 (100 and 300 µM) was administered in human U87 and A172 GBM cell lines. The xCELLigence system was used to examine cell growth when different concentrations of P4 (20, 50, 100, and 300 µM) was administered. The protein profiles were determined by two‐dimensional gel electrophoresis in both cell lines when 100 and 300 µM P4 were administered. Finally, the pathways enriched by the differentially expressed proteins were assessed using bioinformatic tools. Increasing doses of P4 blocked the growth of both GBM cells. We identified 26 and 51 differentially expressed proteins (fc > 2) in A172 and U87 cell lines treated with P4, respectively. Only the pro‐tumorigenic mitochondrial ornithine aminotransferase and anti‐apoptotic mitochondrial 60 kDa heat shock protein were downregulated in A172 cell line and U87 cell line when treated with P4, respectively. Detoxification of reactive oxygen species, cellular response to stress, glucose metabolism, and immunity‐related proteins were altered in P4‐treated GBM cell lines. The paradox on the effect of low and high doses of P4 on GBM growth is gaining attention. The mechanism related to the high dose of P4 on GBM growth can be explained by the alterations in detoxification mechanisms, stress, and immune response and glucose metabolism. P4 suppresses GBM growth and as it is nontoxic in comparison to classical chemotherapeutics, it can be used as a new strategy in GBM treatment in the future.

MALDI-MS imaging methodology was used to show spatial proteomic alterations on YAC128 mice brains. The optimized and improved workflow is suitable for tissue analysis and the acquired results are believed to provide important insights into disease.

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